Dr. Surbhi Gupta holds Ph. D. from IKG Punjab Technical University, Punjab, India. She received merit for her master’s degree at Punjab Agricultural University, Punjab. She is presently working as an Assistant Professor at PAU, Ludhiana, India. Dr. Surbhi has been involved in research on applications of image analysis using machine learning. She has authored over 45+ international journal and conference papers. Her articles appeared in high impact factor journals published by IEEE, Springer etc. She has 100+ citations for her research publications in Web of Science/Scopus/UGC journals. She has been granted one international patent “Fire Detection and Notification Using IOT Based Technology” and has edited book on the topic “Society 5.0” published by Taylor and Francis, CRC Press, United Kingdom.

Education:

• Ph.D. (Computer Science &Engg.), IKG Punjab Technical University, Jalandhar (2018),

• M.Tech. (Computer Science & Engg.), College of Agricultural Engineering and Technology, Punjab Agricultural University, Ludhiana (2004);

• B.Tech. (Computer Science & Engg.), Lala Lajpat Rai Institute of Engg. And Tech., (Punjab Technical University, Jalandhar) (2002);

Position Held:

• Assistant Professor, CSE GRIET, Hyderabad (2019-2021);

• Associate Professor, CSE Chandigarh University, Mohali, (2018-2019);

• Assistant/Associate Professor, CSE, RIEIT / Rayat Bahra University, Mohali (2006-2018);

• Lecturer, CSE GNDEC, Ludhiana (2005-2006)

Field of Specialization: Image Processing, Machine Learning , Generative AI

Research Interests:

• Image processing and analysis

• Computer vision

• Machine Learning

• Generative AI

Publications:

1. Nayak P, Vaheed S, Gupta S and Mohan N. (2023). Predicting students’ academic performance by mining the educational data through machine learning-based classification model. Educ Inf Technol. 28: 14611-14637.

2. Gupta S, Mohan N and Kaushal P (2022). Passive image forensics using universal techniques: a review. Artif Intell Rev. 55: 1629-1679.

3. Gupta S, Mohan N, Nayak P, Nagaraju K C and Madhvi K (2022). Deep vision-based surveillance system to prevent train–elephant collisions. Soft Comput. 26: 4005-4018.

4. Gupta S, Mohan N and Kumar M (2020). A study on source device attribution using still images. Arch Comput Methods Eng. 1-15.

5. Gupta S, Thakur K and Kumar M (2020). 2D-human face recogni